Assessing performance validity is imperative in both clinical and research contexts as data interpretation presupposes adequate participation from examinees. Performance validity tests (PVTs) are utilized to identify instances in which results cannot be interpreted at face value. This study explored the hit rates for two frequently used PVTs in a research sample of individuals with and without histories of bipolar disorder (BD).

As part of an ongoing longitudinal study of individuals with BD, we examined the performance of 736 individuals with BD and 255 individuals with no history of mental health disorder on the Test of Memory Malingering (TOMM) and the California Verbal Learning Test forced choice trial (CVLT-FC) at three time points.

Undiagnosed individuals demonstrated 100% pass rate on PVTs and individuals with BD passed over 98% of the time. A mixed effects model adjusting for relevant demographic variables revealed no significant difference in TOMM scores between the groups, a = .07, SE = .07, p = .31. On the CVLT-FC, no clinically significant differences were observed (ps < .001).

Perfect PVT scores were obtained by the majority of individuals, with no differences in failure rates between groups. The tests have approximately >98% specificity in BD and 100% specificity among non-diagnosed individuals. Further, nearly 90% of individuals with BD obtained perfect scores on both measures, a trend observed at each time point.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.

In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.

Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.

These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Immune system markers may predict affective disorder treatment response, but whether an overall immune system marker predicts bipolar disorder treatment effect is unclear.

Bipolar CHOICE (N = 482) and LiTMUS (N = 283) were similar comparative effectiveness trials treating patients with bipolar disorder for 24 weeks with four different treatment arms (standard-dose lithium, quetiapine, moderate-dose lithium plus optimised personalised treatment (OPT) and OPT without lithium). We performed secondary mixed effects linear regression analyses adjusted for age, gender, smoking and body mass index to investigate relationships between pre-treatment white blood cell (WBC) levels and clinical global impression scale (CGI) response.

Compared to participants with WBC counts of 4.5–10 × 109/l, participants with WBC < 4.5 or WBC ≥ 10 showed similar improvement within each specific treatment arm and in gender-stratified analyses.

An overall immune system marker did not predict differential treatment response to four different treatment approaches for bipolar disorder all lasting 24 weeks.

Major depressive disorder (MDD) is a highly heterogeneous condition in terms of symptom presentation and, likely, underlying pathophysiology. Accordingly, it is possible that only certain individuals with MDD are well-suited to antidepressants. A potentially fruitful approach to parsing this heterogeneity is to focus on promising endophenotypes of depression, such as neuroticism, anhedonia, and cognitive control deficits.

Within an 8-week multisite trial of sertraline v. placebo for depressed adults (n = 216), we examined whether the combination of machine learning with a Personalized Advantage Index (PAI) can generate individualized treatment recommendations on the basis of endophenotype profiles coupled with clinical and demographic characteristics.

Five pre-treatment variables moderated treatment response. Higher depression severity and neuroticism, older age, less impairment in cognitive control, and being employed were each associated with better outcomes to sertraline than placebo. Across 1000 iterations of a 10-fold cross-validation, the PAI model predicted that 31% of the sample would exhibit a clinically meaningful advantage [post-treatment Hamilton Rating Scale for Depression (HRSD) difference ⩾3] with sertraline relative to placebo. Although there were no overall outcome differences between treatment groups (d = 0.15), those identified as optimally suited to sertraline at pre-treatment had better week 8 HRSD scores if randomized to sertraline (10.7) than placebo (14.7) (d = 0.58).

A subset of MDD patients optimally suited to sertraline can be identified on the basis of pre-treatment characteristics. This model must be tested prospectively before it can be used to inform treatment selection. However, findings demonstrate the potential to improve individual outcomes through algorithm-guided treatment recommendations.